Eye gaze tracking has use in a wide range of applications, including medical research, automobile technology, computer entertainment and video game programs, control input devices, augmented reality glasses, and more.
Some known eye gaze tracking techniques involve illuminating the eyes by emitting light from one or more light sources and detecting reflections of the emitted light off of the eyes with a sensor. Typically, this is accomplished using invisible light sources in the infrared range and capturing image data (e.g., images or video) of the illuminated eyes with an infrared sensitive camera. Image processing algorithms are then used to analyze the image data to determine eye gaze direction.
Generally, eye tracking image analysis takes advantage of characteristics distinctive to how light is reflected off of the eyes to determine eye gaze direction from the image. For example, the image may be analyzed to identify eye location based on corneal reflections in the image data, and the image may be further analyzed to determine gaze direction based on a relative location of the pupils in the image.
Two common gaze tracking techniques for determining eye gaze direction based on pupil location are known as Bright Pupil tracking and Dark Pupil tracking. Bright Pupil tracking involves illumination of the eyes with a light source that is substantially in line with the optical axis of the camera, causing the emitted light to be reflected off of the retina and back to the camera through the pupil. The pupil presents in the image as an identifiable bright spot at the location of the pupil, similar to the red eye effect which occurs in images during conventional flash photography. Dark Pupil tracking involves illumination with a light source that is substantially off line from the optical axis of the camera, causing light directed through the pupil to be reflected away from the optical axis of the camera, resulting in an identifiable dark spot in the image at the location of the pupil.
In order to effectively determine the desired eye gaze characteristics (e.g., eye position, gaze direction, and the like), these tracking techniques generally rely on the tracking system's ability to effectively illuminate the user's eyes with the light source and effectively detect the corresponding reflections of the emitted light off of these eyes. However, geometric parameters such as the location of the user with respect to the tracking system sensor and with respect to the light sources of the tracking system can be highly variable, changing with different system setups and even different instances of use of the same tracking system setup.
It would be desirable to have an eye tracking system capable of illuminating eyes and capturing corresponding eye illuminations in a manner that accounts a variety of different geometric parameters. Unfortunately, there is no way to efficiently do so using traditional techniques. It is within this context that aspects of the present disclosure arise.